Nikolay Jetchev

Computer Vision and Pattern Recognition · 2011–2017

A researcher in the Science corpus: 3 papers; trusts 174 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 29 citations into it; #11,432 of 21,575 by trust here, #13,269 by citations
• Generative Models — 19 citations into it; #1,378 of 1,956 by trust here, #1,635 by citations
• Artificial Intelligence — 12 citations into it
• Computer Graphics and Computer-Aided Design — 10 citations into it; #799 of 1,584 by trust here, #807 by citations
• Control and Systems Engineering — 5 citations into it

Whom Nikolay Jetchev trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Alec Radford
3. Sergey Ioffe
4. Alexei A. Efros
5. Javier Portilla
6. Geoffrey E. Hinton
7. Leon A. Gatys
8. Yann LeCun
9. Alex Krizhevsky
10. Christian Szegedy

Who trusts Nikolay Jetchev overall

1. Adrien Baranes
2. Yun Jiang
3. Zhengwei Wang
4. Urs M. Bergmann
5. Jie Gui
6. Eric Laloy
7. Abdul Jabbar
8. Pierre-Yves Oudeyer
9. Marcus Lim
10. Qi She

Papers from Nikolay Jetchev's perspective

Ordered by how strongly the researchers Nikolay Jetchev trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Learning Texture Manifolds with the Periodic Spatial GAN (2017) — 179 citations
• Texture Synthesis with Spatial Generative Adversarial Networks (2016) — 226 citations
• Task Space Retrieval Using Inverse Feedback Control (2011) — 25 citations